Disease resistance in whitebark pine and potential for restoration of a threatened species
Bibliographic record
Abstract
Societal impact statement Forests world‐wide are being negatively affected by non‐native, invasive pathogens and pests, and some tree species face uncertain futures. To retain these species as components of future forests, the rare genetic resistance that exists needs to be identified and harnessed. The applied tree improvement program for whitebark pine ( Pinus albicaulis ), a threatened (in the United States) and endangered (in Canada) keystone species in many forests in western North America, provides an example of what can be accomplished in a relatively short timeframe. The level and frequency of resistance vary by location, and this information will be used to implement the national restoration plan. Summary Forest trees face serious threats from non‐native diseases and pests, often causing high mortality of both the existing trees and regeneration. Developing populations with genetic resistance can help restore forests and retain affected species. Resistance programs have historically focused on species of high economic importance; however, the threats to species of little direct economic value that provide other important ecosystem services are also great. We examined the frequency, level, and geographic variation in genetic resistance to white pine blister rust in the threatened Pinus albicaulis (whitebark pine), a keystone species in high‐elevation ecosystems in western North America. In the two trials reported here, 2‐year‐old seedling progeny of 225 whitebark pine parent trees were inoculated with two geographic sources of the fungal pathogen Cronartium ribicola and evaluated over 5 years for an array of resistance traits. The trials focused primarily on parent trees from the Oregon and Washington populations. We found unexpectedly high levels of quantitative resistance in some seedling families and populations, in stark contrast to levels observed in similar resistance programs with other North American white pine species such as Pinus monticola and Pinus lambertiana . The level of resistance found in some whitebark pine populations provides optimism about potential recovery efforts for this species. Restoration efforts are underway by government agencies, tribes, and non‐government organizations in both the United States and Canada. These efforts may help boost support for applied genetic resistance programs in other forest tree species severely affected by non‐native pathogens or pests.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".